{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import math\n",
    "import logging\n",
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import sklearn\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set_context(\"poster\")\n",
    "sns.set(rc={'figure.figsize': (16, 9.)})\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "import pandas as pd\n",
    "pd.set_option(\"display.max_rows\", 120)\n",
    "pd.set_option(\"display.max_columns\", 120)\n",
    "\n",
    "logging.basicConfig(level=logging.INFO, stream=sys.stdout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from justcause import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**PLEASE** save this file right now using the following naming convention: `NUMBER_FOR_SORTING-YOUR_INITIALS-SHORT_DESCRIPTION`, e.g. `1.0-fw-initial-data-exploration`. Use the number to order the file within the directory according to its usage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
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  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
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